Search and RBS Notes
Rule Based Systems and Search Notes
1. Rule-Based Systems:
General Forward Chaining Pseudo code
1. For all rules, and assertions, find all matches, i.e. Rule+Assertion combinations.
2. Check if any of the matches are defunct.
Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2012
Project("cfw_F184B08F-C81C-45F6-A57F-5ABD9991F28F") = "Random Project", "Random
Project\Random Project.vbproj", "cfw_C1488568-C66F-49A7-A1E5-59F7B6326197"
Algorithmic Trading of Futures via
David Montague, [email protected]
lgorithmic trading of securities has become
a staple of modern approaches to financial
investment. In this project, I attempt to
obtain an effective strategy for trad
History of AI
Origins of AI
McCulloch & Pitts neurons; Hebbs learning rule
Turings Computing Machinery and Intelligence
Shannons computer chess
Georgetown-IBM machine translation experiment
Dartmouth meeting: Artificial I
Game theory deals with systems of interacting
agents where the outcome for an agent depends
on the actions of all the other agents
Applied in sociology, politics, economics, biology, and,
of course, AI
Agent design: determining the best str
Review: Game theory
Pareto optimal outcome
Game of Chicken
S -10, -10
Rational Agents (Chapter 2)
Agent function and agent program
PEAS (Performance measure, Environment, Actuators,
An agent is anything that can be viewed as perceiving its
Knowledge base (KB) = set of sentences in a formal language
Declarative approach to building an agent (or other system):
Tell it what it
Solving problems by searching
We will consider the problem of designing goalbased agents in fully observable, deterministic,
discrete, known environments
We will consider the problem of designing
COMP 590: Artificial Intelligence
What is AI?
Examples of AI today
Who is this course for?
An introductory survey of AI techniques for
students who have not previously had an
exposure to this subject
Juniors, seniors, beginning
Local search algorithms
Some types of search problems can be formulated
in terms of optimization
We dont have a start state, dont care about the path
to a solution
We have an objective function that tells us about
the quality of a possible solution, an
Constraint Satisfaction Problems
Constraint satisfaction problems (CSPs)
State is defined by variables Xi with values from domain Di
Goal test is a set of constraints specifying allowable
combinations of values for subsets of variables
Review: Search problem formulation
What is the optimal solution?
What is the state space?
Review: Tree search
Initialize the fringe using the starting state
While the fringe is not empty
Microsoft Visual Studio Solution File, Format Version 11.00
# Visual Studio 2010
Project("cfw_F184B08F-C81C-45F6-A57F-5ABD9991F28F") = "Debug Project", "Debug
Project\Debug Project.vbproj", "cfw_AF297039-B285-4B20-AEA3-C7314B50A2E1"
In the name of God
HW SET # 1
(1) A farmer has a goat, a wolf and a cabbage on the west side of a river. He wants to get all
of his animals and his cabbage acrossthe river onto the east side. The farmer has a row boat
but he only has enough room for h
THE FONDA THEATRE
6125 HOLLYWOOD BLVD, LA
DOORS @ 8:00PM
Thursday, August 15, 2013 AT 9:00 PM
TICKET: $ 18.50 + $ 2.50 + $ 7.50
Fold here. Do not detach.
Fold here. Do not detach.
To work on this problem set, you will need to get the code:
This lab has two parts; the first part is on CSPs and the second part is on learning algorithms,
specifically KNN and decision trees.
Constraint Satisfaction Problems
In this portion of Lab
To work on this problem set, you will need to get the code, much like you did for earlier problem sets.
Your answers for the problem set belong in the main file lab3.py.
This problem set is about game search, and it will focus on the gam
Games and CSP Notes
Games and CSP search
A) General Minimax search:
function max-value(state, depth)
1. if state is an end-state (end of game) or depth is 0
2. v = -infinity
3. for s in get-all-next-moves(state)
v = max(v, min-v
This is the last problem set in 6.034! To work on this problem set, you will need to get the code.
You will need to download and install an additional software package called Orange for the second
part of the lab. Please download Orange first so tha
Top Down Approach To Neural Nets
MAJOR HINT for Neural Nets portion of Lab 5
Figure 1: A two layer Neural Network
To understand what to implement for dOutDx(self, weight) for lab 5, you'll need to
thoroughly understand how the error update equation for ba
KNN-ID and Neural Nets
KNN, ID Trees, and Neural Nets
Intro to Learning Algorithms
KNN, Decision trees, Neural Nets are all supervised learning algorithms
Their general goal = make accurate predictions about unknown data after being trained on known
Probability, Bayes Nets, Naive Bayes, Model Selection
Intro to Bayes nets: what they are and what they represent.
How to compute the joint probability from the Bayes net.
How to compute the conditional prob
To work on this problem set, you will need to get the code, much like you did for Lab 0.
Most of your answers belong in the main file lab1.py. However, the more involved coding problems
in section 2 have their own separate files.
You will probably w
SVM and Boosting
Support Vector Machines
In SVMs we are trying to find a decision boundary that maximizes the "margin" or the "width of
the road" separating the positives from the negative training data points.
To find this we minimize:
subject to the con
The purpose of this lab is to familiarize you with this term's lab system and to diagnose your
programming ability and facility with Python. 6.034 uses Python for all of its labs, and you will be
called on to understand the functioning of large syst
Please make the following corrections in your textbook
Page 2.15 - In the first paragraph below form W-2 Wage and Tax Statement, change Illustration 2.12 to
Page 2.16 - In the paragraph below Specific Form W-2 Box Information change Illustration 2.11
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